A note on Rebonato and Jäckel's parametrization method for
finding nearest correlation matrices

Alec N. Kercheval

Portfolio risk forecasts are often made by estimating an asset or
factor correlation matrix. However, estimation difficulties or
exogenous constraints can lead to correlation matrix candidates that
are not positive semidefinite (psd). Therefore, practitioners need to
reimpose the psd property with the minimum possible
correction. Rebonato and J?ackel (2000) raised this question and
proposed an approach; in this paper we improve on that approach by
introducing a more geometric perspective on the problem.